README.md

---
license: mit
tags:
- pde-probe-pilot
- probe
- last_tok
- linear-probe
---

# pde-probe-pilot-probe-pooled-last-tok-v1

LOGO-CV pooled linear probe results (last_tok), all labels × all 29 layers. 128 rows, 8 mod_types. Complete.

## Dataset Info

- **Rows**: 270
- **Columns**: 17

## Columns

| Column | Type | Description |
|--------|------|-------------|
| label | Value('large_string') | Target label probed (pde_class, process_*, method_*, phys_valid) |
| layer | Value('large_string') | Transformer layer index (0=embedding, 1-28=transformer) or 'bow' |
| pool | Value('large_string') | Pooling strategy (last_tok) |
| accuracy | Value('float64') | LOGO-CV mean accuracy across 16 folds |
| ci_low | Value('float64') | Bootstrap 95% CI lower bound (n=10,000 resamples) |
| ci_high | Value('float64') | Bootstrap 95% CI upper bound |
| mt_Comm_Valid | Value('float64') | *No description provided* |
| mt_NoComm_Valid | Value('float64') | *No description provided* |
| mt_CorrComm | Value('float64') | *No description provided* |
| mt_NoComm_CorrVar | Value('float64') | *No description provided* |
| mt_Comm_InValid | Value('float64') | *No description provided* |
| mt_NoComm_InValid | Value('float64') | *No description provided* |
| mt_CorrComm_Invalid | Value('float64') | *No description provided* |
| mt_NoComm_CorrVar_InValid | Value('float64') | *No description provided* |
| auroc | Value('float64') | LOGO-CV mean AUROC (binary labels only; NaN for pde_class) |
| auroc_ci_low | Value('float64') | Bootstrap 95% CI lower bound for AUROC |
| auroc_ci_high | Value('float64') | Bootstrap 95% CI upper bound for AUROC |


## Generation Parameters

```json
{
  "script_name": "probe/linear_probe_pooled.py",
  "model": "Qwen/Qwen2.5-Coder-7B-Instruct",
  "description": "LOGO-CV pooled linear probe results (last_tok), all labels \u00d7 all 29 layers. 128 rows, 8 mod_types. Complete.",
  "experiment_name": "pde-probe-pilot",
  "job_id": "torch:7242668",
  "cluster": "torch",
  "artifact_status": "final",
  "canary": false,
  "hyperparameters": {
    "pooling": "last_tok",
    "cv": "LOGO-CV",
    "n_folds": 16
  },
  "input_datasets": []
}
```

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("rosubramanian/pde-probe-pilot-probe-pooled-last-tok-v1", split="train")
print(f"Loaded {len(dataset)} rows")
```

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